Soft-Thresholding and Shrinkage. Images are inherently sparse in the Fourier domain, and most of the energy is concentrated around low frequency modes. Thus, one can adaptively mask the tokens according to their importance towards the end task. This can use the expressivity towards representing the important tokens. To sparsify the tokens, instead of linear combination as in (REF ), we use the nonlinear LASSO [1]} channel mixing as follow
\(\min \Vert \tilde{z}_{m,n}-W_{m,n}z_{m,n}\Vert ^2 + \lambda \Vert \tilde{z}_{m,n}\Vert _1\) 
